boschresearch / numerics_independent_neural_odes
Code accompanying the ICLR 2021 paper "ResNet After All? Neural ODEs and Their Numerical Solution"
☆9Updated 2 years ago
Alternatives and similar repositories for numerics_independent_neural_odes
Users that are interested in numerics_independent_neural_odes are comparing it to the libraries listed below
Sorting:
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- ☆21Updated 6 months ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Deterministic particle dynamics for simulating Fokker-Planck probability flows☆24Updated 2 years ago
- ☆10Updated 3 years ago
- Port-Hamiltonian Approach to Neural Network Training☆24Updated 5 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 7 months ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆50Updated last year
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆52Updated 2 years ago
- SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations☆21Updated 2 years ago
- Code for "Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference" (ICML 2024)☆16Updated 5 months ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Deep Bayesian Optimization for Problems with High-Dimensional Structure☆16Updated 2 years ago
- ☆38Updated 3 years ago
- Repository for Deterministic Particle Flow Control framework☆10Updated 2 years ago
- Code for the paper "Rational neural networks", NeurIPS 2020☆28Updated 4 years ago
- code for "Neural Jump Ordinary Differential Equations"☆30Updated 2 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆38Updated 2 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆38Updated 3 weeks ago
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆10Updated 2 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆55Updated 2 years ago
- Library for normalizing flows and neural flows.☆24Updated 2 years ago
- ☆29Updated 2 years ago
- ☆27Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 3 years ago
- This repository contains code released by DiffEqML Research☆90Updated 3 years ago